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Announcing HDF5 for Python (h5py) 1.1
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What is h5py?
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HDF5 for Python (h5py) is a general-purpose Python interface to the
Hierarchical Data Format library, version 5. HDF5 is a versatile,
mature scientific software library designed for the fast, flexible
storage of enormous amounts of data.
>From a Python programmer's perspective, HDF5 provides a robust way to
store data, organized by name in a tree-like fashion. You can create
datasets (arrays on disk) hundreds of gigabytes in size, and perform
random-access I/O on desired sections. Datasets are organized in a
filesystem-like hierarchy using containers called "groups", and
accesed using the tradional POSIX /path/to/resource syntax.
In addition to providing interoperability with existing HDF5 datasets
and platforms, h5py is a convienient way to store and retrieve
arbitrary NumPy data and metadata.
New features in 1.1
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- A new compression filter based on the LZF library, which provides
transparent compression many times faster than the standard HDF5
GZIP filter.
- Efficient broadcasting using HDF5 hyperslab selections; for example,
you can write to a (2000 x 100 x 50) selection from a (100 x 50)
source array.
- Now supports the NumPy boolean type
- Auto-completion for IPython 0.9.X (contributed by Darren Dale)
- Installable via easy_install
Standard features
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- Supports storage of NumPy data of the following types:
* Integer/Unsigned Integer
* Float/Double
* Complex/Double Complex
* Compound ("recarray")
* Strings
* Boolean
* Array (as members of a compound type only)
* Void
- Random access to datasets using the standard NumPy slicing syntax,
including fancy indexing and point-based selection
- Transparent compression of datasets using GZIP, LZF or SZIP,
and error-detection using Fletcher32
- "Pythonic" interface supporting dictionary and NumPy-array metaphors
for the high-level HDF5 abstrations like groups and datasets
- A comprehensive, object-oriented wrapping of the HDF5 low-level C API
via Cython, in addition to the NumPy-like high-level interface.
- Supports many new features of HDF5 1.8, including recursive iteration
over entire files and in-library copy operations on the file tree
- Thread-safe
Where to get it
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* Main website, documentation: http://h5py.alfven.org
* Downloads, bug tracker: http://h5py.googlecode.com
Requires
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* Linux, Mac OS-X or Windows
* Python 2.5 (Windows), Python 2.5 or 2.6 (Linux/Mac OS-X)
* NumPy 1.0.3 or later
* HDF5 1.6.5 or later (including 1.8); HDF5 is included with
the Windows version.
Thanks
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Thanks to D. Dale, E. Lawrence and other for their continued support
and comments. Also thanks to the Francesc Alted and the PyTables project,
for inspiration and generously providing their code to the community. Thanks
to everyone at the HDF Group for creating such a useful piece of software.